Cardiovascular Journal of Africa: Vol 31 No 1 (January/February 2020)

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CARDIOVASCULAR JOURNAL OF AFRICA • Volume 31, No 1, January/February 2020 AFRICA 53
taking into consideration the associated risk factors. The study,
however, has a few limitations. First, while the study sample
was large enough to allow credible estimates of hypertension
at the national level, the samples at the district level were not
large enough and this resulted in wide confidence intervals for
the estimated prevalence rates. Second, although we adjusted
for seasonal variation when BP measurements were taken for
each subject, it was not possible to fully adjust for ambient
temperatures since these measurements were not available in our
data set.
Third, although we adjusted for race in the analysis, it is
possible that there could be differences within the same race,
especially for black South Africans, who are also characterised
by different ethnicities/tribes. The data set did not have details
on ethnicity or tribe. A few studies in sub-Saharan Africa have
shown variability of hypertension by ethnicity. In Nigeria,
prevalence of hypertension was found to differ significantly
by ethnicity after adjusting for age, gender, place of residence
and socio-economic status.43 Similarly, some evidence of
ethnic variation has been reported in Kenya where statistically
significant differences between ethnic groups were reported
after adjusting for sociodemographic and other cardiovascular
risk factors,44 but a study from Nigeria and Cameroon did not
find any association of hypertension with ethnicity.45 It may
be interesting to analyse other aspects of diet and cultural
differences in food intake, such as salt and sugar consumption,
both of which were not available in our data set, and are known
for their strong influence on hypertension.
Conclusions
The results from this study show that there were significant
differences in the prevalence of hypertension at the district level.
Districts with a higher-than-average prevalence appeared to
be clustered together, as were those with a lower-than-average
prevalence. An implication of these results is that there could
have been other risk factors not captured in the data that
were associated with hypertension prevalence and were also
distributed unequally between the districts.
It could also mean that there were differentials in the
clusters of districts in prevention, management and control of
hypertension. Effective management without complete control
could imply people living longer with the condition, thereby
increasing the prevalence of hypertension. On the other hand,
districts with a low prevalence could indicate poor management,
which could result in hypertension-related deaths. Alternatively,
low prevalence could be a result of either low incidence or
effective prevention and control interventions. These could
be issues for further related research and in particular an
examination of the impact of district-level covariates/factors.
The data sets analysed during the current study are available in the NiDS
DataFirst repository:
catalog/NIDS. We acknowledge the NiDS for providing access to data used
for this study.
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